1. Factory Performance Optimization
Methods and tools for continuous significant improvement of
production and operations

2. SIMANDO is a global management and technology consulting firm with a high
focus on decision support systems and operational excellence. We partner with
client organizations in all industrial sectors to address their most important
challenges and develop complete solutions that will enable them to achieve
their objectives and make significant improvements in their performance. Our
customized approach combines innovative technology, systems thinking and
passion for operational excellence. This ensures that our solutions enable our
clients to achieve sustainable competitive advantage by optimized operations
and responsiveness to the current dynamic business environment.
Founded in 2009, SIMANDO is a private company with its headquarters in
Timisoara, Romania. For more information, please visit:
www.simando.com

3. Outline
 About SIMANDO
 Services and Products
 Factory Performance Optimization Framework
 Analytical Methods for Performance Analysis & Improvement
 Simulation in Manufacturing
 Lean Six Sigma for Manufacturing
2011 3/35

4. About SIMANDO
Company founded in 2009
Privately owned, LLC
Headquarters: Timisoara, ROMANIA
Mission
At SIMANDO, our primary mission is to help our clients make substantial, continuous improvement in their performance. We
accomplish this by providing them with outstanding technology solutions and consulting services to increase their excellence
degree at all levels.
Vision
We strive to be the company that understands perfectly its clients' objectives, always delivers quantifiable results and
maximizes the financial and trust investments made by its clients.
Our Certifications
Certified Six Sigma Black Belt Project Management Professional
(American Society for Quality) (Project Management Institute)
Certificate in Finance Oracle Certified Professional Java
(New York Institute of Finance) Programmer
(Oracle Corporation)
2011 4/35

5. Expertise
Modeling and Simulation Operational Excellence
 Systems modeling, simulation and optimization  Lean Six Sigma Transformation
 All simulation paradigms - discrete events, agent-  Design for Six Sigma
based and system dynamics
 Toyota Production System
 Statistics
 Theory of Constraints
 Product Development
Software Applications Development Industrial
 Advanced algorithms and design patterns  Project and product development management
 Software architecture
 Computer Integrated Manufacturing
 Software development lifecycle methodologies
 Industrial engineering and factory planning
 Functional and object oriented programming
 Manufacturing, logistics, supply chain design
 Database Management Systems
 Transport and distribution systems
 MRP/ERP Systems
2011 5/35

6. Services and Products
 Services
 Production, logistics, supply chain, healthcare engineering , modelling and simulation
 Operations optimization
 Lean Six Sigma/Design For Six Sigma training and implementation
 Training and assistance in simulation models development
 Product development and project management
 Computer Integrated Manufacturing
 Products
 Modeling and simulation component libraries
 MANSIM™ - general manufacturing
 SOLSIM ™ - photovoltaics manufacturing equipment
 LOGSIM ™ - warehousing and logistics
 Specialized software applications for Lean Six Sigma, planning and scheduling
2011 6/35

7. Factory Performance Optimization
Industrial
Engineering
Information
Six Sigma
Technology
Factory
Performance
TRIZ Lean
Theory of
Constraints
Synergistic framework for continuous significant improvement of production and operations
2011 7/35

8. Factory Performance Leverage Points
1st Dimension
1st Dimension
Products and processes selection
Factory location, size and layout
2nd Dimension
Factory workstations and machines
Factory personnel
Material handling systems
Supplies and spare parts inventory 2nd Dimension
Degree of automation
3nd Dimension
Jobs starts protocol
Preventive maintenance protocols
Personnel allocation protocols
Batching protocols
Dispatching rules and scheduling
Waste reduction programs
The 3 Dimensions of Manufacturing 3rd Dimension
Investment
Manufacturing Performance
2011 8/35

9. Factory Performance Indicators
 Little’s Law • Performance Curves
𝑊𝐼𝑃 = 𝐶𝑇 × 𝑇𝐻 Cycle Time vs. Loading
LACTE
Profit vs. Loading
 P-K Equation
𝐶2 + 𝐶2
𝐴𝑅 𝐸𝑃𝑇 𝜌 2(𝑚+1)−1
1 1
𝐶𝑇 𝑝𝑠 = +
2 𝑚(1 − 𝜌) 𝐸𝑃𝑅 𝑝𝑠 𝐸𝑃𝑅 𝑝𝑠
 Propagation of Variability
𝜌2
𝐶 2 = 1 + 1 − 𝜌2
𝐷𝑅 𝐶2 − 1 +
𝐴𝑅 𝐶2 − 1
𝐸𝑃𝑇
𝑚
 Capacity Effectiveness
𝐷 𝑊0 𝑄1
𝐸𝐶 = 1− ×
𝑟𝑏 𝑁𝑊𝑃
2011 9/35

10. Why Simulation ?
What?
Where? Who? The future is of greater interest
to me than the past, since that
is where I intend to spend the
! rest of my life.
When? Why? ~ Albert Einstein
How?
BECAUSE … SIMULATION GIVES US ANSWERS!
2011 10/35

11. Simulation Study Types
Simulation
Studies
System Design Problem Solving Continuous Improvement
 New processes  Diagnosis  Opportunity definition
 New facilities  Problem definition  Performance measurement
 New concepts  Solution finding  Performance improvement
Structural Design Diagnosis Opportunity Definition
 Elements  Problem definition  Benchmarking
 Layout
 Logic
Logical Design Testing Schemes Test Plans
 Flow logic  What-if scenarios analysis  Feasibility check
 Operations sequences
 Priority rules
Parametric Design Solution Validation Plan Validation
 Cycle times  Sensitivity analysis  Sensitivity analysis
 Reliability requirements
 Velocities, rates
2011 11/35

12. Simulation Benefits
Analyze the behavior of
Experiment and get complex systems
Make prompt and
fast feedback
correct decisions
Convince clients of your
operational capabilities Communicate ideas
efficiently and credibly
Teach new Test fast, fail fast, adjust fast.
concepts easily
~ Tom Peters
Discover alternatives to
unexpected roadblocks
Save money in short
and medium term
Safely analyze
dangerous scenarios Implement your decisions
with confidence
2011 12/35

13. Applicability Areas
Manufacturing Lean Six Sigma Logistics and Supply Chain
 Key Performance Indicators  Stochastic process simulation
 FMEA  Statistical analysis  Transport networks design
 Production flow design  Variability elimination  Fleet planning & maintenance
 Planning and scheduling  Pull mechanism design  Warehouse design
 Resource estimation  QOS metrics  Operations optimization
 Capacity planning  Dynamic VSM  Supply chain planning
 Total cost of ownership  Benchmarking
Healthcare IT & Telecom Urban Development
 Resource estimation  Wireless networks topology
 Public utilities planning
 QOS  Protocols design  Evacuation plans creation
 Epidemics dynamics  Agent-based emergent  Disaster recovery
 Operations optimization behaviour analysis  Anti-terrorist measures
 QOS
2011 13/35

14. How We Do It ?
Continuous improvement is better
than delayed perfection.
~ Mark Twain
Problem formulation
Objectives and plan definition
Control
Model conceptualization
Data collection
Your trajectory to success Implementation
with simulation
Reporting
Model development
Experiments run and analysis
Code verification
Design of experiments
Model validation
2011 14/35

15. Modeling
Reusable models and components encourage continuous improvement!
Specialized
component
libraries
2D/3D
customizable
animation
Domain specific
library components
Fast and easy
drag-and-drop
layout modeling
2011 15/35

16. Simulation Models Input/Output Data
CAD Run-time Charts
Text Text
Excel Excel
XML Simulation Model XML
Input Output
Database Database
Data Data
Webservice Webservice
2011 16/35

17. Simulation in Manufacturing
Creativity is thinking up new things.
Innovation is doing new things.
Assembly line simulation model
( http://simando.com/resources/applications/35 ) ~ Ted Levitt
2011 17/35

18. Simulation in Manufacturing
 Optimal plant layout
?
2011 18/35

19. Simulation in Manufacturing
 Detection and management of bottlenecks
?
120 sec
30 sec
120 sec Rework Loop
120 sec
A
60 sec
120 sec Rework Loop
B 60 sec
120 sec
60 sec
120 sec Rework Loop
2011 19/35

20. Simulation in Manufacturing
 Equipment ROI Calculation
Golden Equipment Silver Equipment Bronze Equipment
Cycle Time ………....... 30 sec Cycle Time ………....... 60 sec Cycle Time ………....... 80 sec
MTBF_1 …..………… 5000 hrs MTBF_1 …..………… 4000 hrs MTBF_1 …..………… 5000 hrs
MTTR_1 ……………........ 1 hrs MTTR_1 ……………........ 2 hrs MTTR_1 ……………........ 1 hrs
MTBF_2 ……………… 7500 hrs MTBF_2 ……………… 8500 hrs MTBF_2 ……………… 8000 hrs
MTTR_2 ………………… 0.5 hrs MTTR_2 ………………… 3 hrs MTTR_2 ………………… 2 hrs
Yield ………………………. 99.6% Yield ………………………. 98.9% Yield ………………………. 97.2%
Energy …………………. 10 kWh Energy …………………. 8 kWh Energy …………………. 14 kWh
Price …………….… $1,500,000 Price ……………….… $850,000 Price ……………….… $450,000
2011 20/35

21. Simulation in Manufacturing
 Total Cost of Ownership
𝑻𝒐𝒕𝒂𝒍 𝑪𝒐𝒔𝒕𝒔 ($)
𝑻𝑪𝑶 =
𝑻𝒐𝒕𝒂𝒍 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑮𝒐𝒐𝒅 𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒔 𝑶𝒗𝒆𝒓 𝑺𝒚𝒔𝒕𝒆𝒎′ 𝒔 𝑳𝒊𝒇𝒆
𝑻𝒐𝒕𝒂𝒍 𝑪𝒐𝒔𝒕𝒔($) = 𝑭($) + 𝑳($) + 𝑹($) + 𝒀($)
Where:
F ($) = fixed costs for purchasing the system
L ($) = fully burdened labor cost
R ($) = recurring costs (consumables, maintenance, specialized support etc.)
Y ($) = yield loss cost
𝒀($) = 𝑵 ∗ 𝑷($)
Where:
N = number of defective product entities
P ($) = value of the product entities in the specific production stage
2011 21/35

22. Simulation in Manufacturing
 Total Cost of Ownership
𝑻𝒐𝒕𝒂𝒍 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑮𝒐𝒐𝒅 𝑷𝒓𝒐𝒅𝒖𝒄𝒕 𝑬𝒏𝒕𝒊𝒕𝒊𝒆𝒔 = 𝑳 ∗ 𝑻 ∗ 𝒀 ∗ 𝑼
𝑷𝒓𝒐𝒅𝒖𝒄𝒆𝒅 𝑶𝒗𝒆𝒓 𝒕𝒉𝒆 𝑺𝒚𝒔𝒕𝒆𝒎′ 𝒔 𝑳𝒊𝒇𝒆
Where:
L = lifetime of the production system
T = throughput rate
Y = composite yield
U = equipment utilization
Where:
SM = scheduled maintenance
USM = unscheduled maintenance
A = assist time
S = standby time
Q = qualification time 𝑺𝑴 + 𝑼𝑺𝑴 + 𝑨 + 𝑺 + 𝑸
𝑼= 𝟏 −
H = total number of scheduled 𝑯
production hours per week
2011 22/35

23. Simulation in Manufacturing
 Total Cost of Ownership
𝑭 $ + 𝑳 $ + 𝑹 $ + 𝒀($)
𝑻𝑪𝑶 =
𝑳∗ 𝑻∗ 𝒀∗ 𝑼
 All variable/probabilistic elements in the formula can be tracked
and calculated by simulating realistically the system under study.
Due to variable costs and probabilistic events associated with complex
production systems, only simulation-based methods of calculating the TCO can
provide correct and accurate estimates therefore.
2011 23/35

24. Simulation in Manufacturing
 Detailed modeling of components and manufacturing scenarios
 Accurate timing and behavior of the modeled systems
 Manual work, worker-machine and fully automated manufacturing modeling possibilities
 Any type of production environment: jobbing, intermittent, mass production
 Resources behavior controlled by highly detailed state machines according to machine specs
 Any type of Key Performance Indicator can be defined and tracked
 Ramp-up scenarios analysis
 Inbound/outbound logistics and supply chain analysis and integration
 Declustering of job starts and maintenance
 Load management scheme design
2011 24/35

25. Simulation in Manufacturing
 Line balancing and materials handling
 Dispatching rules:
 critical ratio, shortest processing time, FIFO, due date, etc.
 Conveyors vs. Automated Guided Vehicles vs. Humans
 Material flow optimization
 Buffers capacities & policies (FIFO, LIFO, FEFO, custom)
2011 25/35

26. Simulation in Manufacturing
 Lean manufacturing speed and quantity control and Six Sigma quality
 Simulation offers support in finding solutions to reduce:
 Transport time
 Inventory and buffers
 Employee motion
 Waiting
 Overproduction
 Defects
2011 26/35

27. Simulation in Manufacturing
 Optimization of Key Performance Indicators
 Work in process (WIP)
 Load-adjusted cycle time efficiency
 Manufacturing lead time
 Equipment cycle times
 Queuing, blocking, waiting, transport time
 Throughput
 Equipment and human resources utilization
 Energy, consumables, spare parts, waste
 Spares and supplies inventory levels and variability
2011 27/35

28. Simulation in Manufacturing
 Design and optimization of complex equipment
 Utilization, throughput, cycle time for cluster tools
 Equipment with M:N mapping of process resources to handling units
 Optimization of handling units movement and process resources allocation
Process Process Process Chambers
Chamber Chamber
Process
Chamber
Multiple handling
units on the same rail IO Ports
Process
Chamber
Process Process
Chamber Chamber
2011 28/35

29. Simulation in Manufacturing
 Production planning and scheduling
Feedback
Simulation
Production Forecast
Planning
2011 29/35

30. Simulation in Lean Implementation
Static Value Stream Map
Nature does constant value stream
mapping – it's called evolution.
~ Carrie Latet
Dynamic Value Stream Map (Simulation)
2011 30/35

31. Simulation in Lean Implementation
 Single piece flow vs. batch processing analysis
 Kanban (pull) mechanism design
 Production leveling (heijunka)
 Cycle, safety and buffer stocks calculation
 Just In Time (JIT), Just in Sequence (JIS) inventory strategy design
 Cellular operations design
 Overall Equipment Effectiveness (OEE) calculation
 Relation between demand and takt time analysis
2011 31/35

32. Simulation in Lean Six Sigma
Define Define Define
Define Project
Scope
Lean
Measures
Structure
and Variables
Develop Develop Identify Sources
Measure Current State
VSM
Develop
Simulation Model
Dynamic
VSM
of Variation and
Waste
Analize Develop DOE Plan
Run Simulation
Experiments
Analyze Process
Flow
Apply Develop
Improve Optimize Process
Parameters
Lean
Techniques
Validate
Improvement
Future State
VSM
Test Implement Monitor
Control Develop Control
Strategy
Control
Plans
Control
Plans
Performance Over
Time
Simulation-based Lean Six Sigma Project Roadmap
2011 32/35

33. Design For Six Sigma
Cost vs. Impact Cost
Potential is negative
(Impact < Cost)
Potential is positive
(Impact > Cost)
Impact
Time
Design Produce/Build Deliver Support
Impact of design stages on life cycle
2011 33/35

34. Simulation in Design For Six Sigma
Identify Simulation-based DFSS Project Roadmap
Model building Data collection
Conceptualize Simulation model
No
Verified ?
Optimize No
Yes
Valid ?
Model analysis
Validate Conclusions and reporting
2011 34/35

35. Thank you for your attention!
SIMANDO Team
SIMANDO LLC
9 Republicii Blvd
Timisoara, TM 300159
ROMANIA
Tel: +40 356 172 021
Fax: +40 356 172 017
E-mail: info@simando.com
Web: www.simando.com